# Copyright 2025 - Oumi
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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from typing_extensions import override

from oumi.core.datasets import VisionLanguageSftDataset
from oumi.core.registry import register_dataset
from oumi.core.types.conversation import (
    ContentItem,
    Conversation,
    Message,
    Role,
    Type,
)


@register_dataset("HuggingFaceM4/Docmatix")
class DocmatixDataset(VisionLanguageSftDataset):
    """Dataset class for the `HuggingFaceM4/Docmatix` dataset."""

    default_dataset = "HuggingFaceM4/Docmatix"

    @override
    def transform_conversation(self, example: dict) -> Conversation:
        """Transform a single conversation example into a Conversation object."""
        input_text = example["question"]
        output_text = example["answer"]

        user_items: list[ContentItem] = []

        if "image_bytes" in example:
            user_items.append(
                ContentItem(
                    binary=example["image_bytes"],
                    type=Type.IMAGE_BINARY,
                )
            )
        elif "image_path" in example:
            user_items.append(
                ContentItem(
                    content=example["image_path"],
                    type=Type.IMAGE_PATH,
                )
            )
        else:
            raise ValueError(
                "Training example contains none of required keys: "
                "'image_bytes', 'image_path'. "
                f"Available keys: {example.keys()}."
            )

        user_items.append(ContentItem(type=Type.TEXT, content=input_text))

        return Conversation(
            messages=[
                Message(role=Role.USER, content=user_items),
                Message(role=Role.ASSISTANT, content=output_text),
            ]
        )
